add private resullts for Vultur

[Samoed]

Checklist

• My model has a model sheet, report, or similar
• My model has a reference implementation in mteb/models/model_implementations/, this can be as an API. Instruction on how to add a model can be found here
  • No, but there is an existing PR ___
• The results submitted are obtained using the reference implementation
• My model is available, either as a publicly accessible API or publicly on e.g., Huggingface
• I solemnly swear that for all results submitted I have not trained on the evaluation dataset including training splits. If I have, I have disclosed it clearly.

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Model Results Comparison

Reference models: intfloat/multilingual-e5-large, google/gemini-embedding-001
New models evaluated: vultr/VultronRetrieverCore-Qwen3.5-4.5B, vultr/VultronRetrieverPrime-Qwen3.5-8B

Results for vultr/VultronRetrieverCore-Qwen3.5-4.5B

task_name	vultr/VultronRetrieverCore-Qwen3.5-4.5B	Max result	Model with max result	In Training Data
Vidore3NuclearRetrieval	.549	.538	nvidia/nemotron-colembed-vl-8b-v2	False
Vidore3TelecomRetrieval	.711	.720	nvidia/nemotron-colembed-vl-8b-v2	False
Average	.630	.629	nan	-

Model have high performance on these tasks: Vidore3NuclearRetrieval

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Results for vultr/VultronRetrieverPrime-Qwen3.5-8B

task_name	vultr/VultronRetrieverPrime-Qwen3.5-8B	Max result	Model with max result	In Training Data
Vidore3NuclearRetrieval	.536	.538	nvidia/nemotron-colembed-vl-8b-v2	False
Vidore3TelecomRetrieval	.713	.720	nvidia/nemotron-colembed-vl-8b-v2	False
Average	.624	.629	nan	-

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